Inflow data with point cloud support.

Attributes¶

states_coord: str

The states coordinate name in the data

point_coord: str

The point coordinate name in the data

x_ncvar: str

The x variable name in the data

y_ncvar: str

The y variable name in the data

h_ncvar: str, optional

The height variable name in the data

weight_ncvar: str, optional

The name of the weights variable in the data

Examples¶

Example of the NetCDF input files with point cloud data:

>>>    Dimensions:  (point: 30, state: 100)
>>>    Dimensions without coordinates: point, state
>>>    Data variables:
>>>        x        (point) float32 120B ...
>>>        y        (point) float32 120B ...
>>>        ws       (state, point) float32 12kB ...
>>>        wd       (state, point) float32 12kB ...
>>>        ti       (point) float32 120B ...
>>>        rho      (state) float32 400B ...

Public members¶

PointCloudData(*args, states_coord='Time', point_coord='point', ...)[source]

Constructor.

__repr__()[source]

Return repr(self).

load_data(algo, verbosity=0)[source]

Load and/or create all model data that is subject to chunking.

interpolate_data(idims, icrds, d, pts, vrs, times)[source]

Interpolates data to points.

property data_source

The data source

preproc_first(algo, data, cmap, vars, bounds_extra_space, ...)[source]

Preprocesses the first file.

gen_states_split_size()[source]

Generator for suggested states split sizes for output writing.

set_running(algo, data_stash, sel=None, isel=None, verbosity=0)[source]

Sets this model status to running, and moves all large data to stash.

unset_running(algo, data_stash, sel=None, isel=None, verbosity=0)[source]

Sets this model status to not running, recovering large data from stash

output_point_vars(algo)[source]

The variables which are being modified by the model.

size()[source]

The total number of states.

index()[source]

The index list

get_calc_data(mdata, cmap, variables)[source]

Gathers data for calculations.

calculate(algo, mdata, fdata, tdata)[source]

The main model calculation.

reset(algo=None, states_sel=None, states_loc=None, verbosity=0)[source]

Reset the states, optionally select states

classmethod new(states_type, *args, **kwargs)[source]

Run-time states factory.

output_coords()[source]

Gets the coordinates of all output arrays

ensure_output_vars(algo, tdata)[source]

Ensures that the output variables are present in the target data.

run_calculation(algo, *data, out_vars, **calc_pars)[source]

Starts the model calculation in parallel.

property model_id

Unique id based on the model type.

var(v)[source]

Creates a model specific variable name.

unvar(vnm)[source]

Translates model specific variable name to origninal variable name.

property initialized

Initialization flag.

sub_models()[source]

List of all sub-models

initialize(algo, verbosity=0, force=False)[source]

Initializes the model.

property running

Flag for currently running models

finalize(algo, verbosity=0)[source]

Finalizes the model.

get_data(variable, target, lookup='smfp', mdata=None, ...)[source]

Getter for a data entry in the model object or provided data sources